US7706600B2 - Enhanced virtual navigation and examination - Google Patents

Enhanced virtual navigation and examination Download PDF

Info

Publication number
US7706600B2
US7706600B2 US10/380,210 US38021005A US7706600B2 US 7706600 B2 US7706600 B2 US 7706600B2 US 38021005 A US38021005 A US 38021005A US 7706600 B2 US7706600 B2 US 7706600B2
Authority
US
United States
Prior art keywords
voxels
intersection
regions
air
region
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related, expires
Application number
US10/380,210
Other languages
English (en)
Other versions
US20070003131A1 (en
Inventor
Kevin Kreeger
Sarang Lakare
Zhenrong Liang
Mark R. Wax
Ingmar Bitter
Frank Dachille
Dongqing Chen
Arie E. Kaufman
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Research Foundation of State University of New York
Original Assignee
Research Foundation of State University of New York
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Research Foundation of State University of New York filed Critical Research Foundation of State University of New York
Priority to US10/380,210 priority Critical patent/US7706600B2/en
Assigned to THE RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK reassignment THE RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: CHEN, DONGQUING, DACHILLE, FRANK, KREEGER, KEVIN, BITTER, INGMAR, LIANG, ZHENGRONG, KAUFMAN, ARIE E., LAKARE, SARANG, WAX, MARK R.
Assigned to RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK, THE reassignment RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK, THE ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: CHEN, DONGQUING, DACHILLE, FRANK, KREEGER, KEVIN, BITTER, INGMAR, LIANG, ZHENGRONG, KAUFMAN, ARIE E., LAKARE, SARANG, WAX, MARK R.
Assigned to NAVY, UNITED STATES OF AMERICA, THE, AS REPRESENTED BY THE SECRETARY reassignment NAVY, UNITED STATES OF AMERICA, THE, AS REPRESENTED BY THE SECRETARY CONFIRMATORY LICENSE (SEE DOCUMENT FOR DETAILS). Assignors: NEW YORK, STATE UNIVERSITY OF
Publication of US20070003131A1 publication Critical patent/US20070003131A1/en
Application granted granted Critical
Publication of US7706600B2 publication Critical patent/US7706600B2/en
Expired - Fee Related legal-status Critical Current
Adjusted expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00—Manipulating 3D models or images for computer graphics
    • G06T19/20—Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/08—Volume rendering
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/10—Geometric effects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/12—Edge-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/64—Analysis of geometric attributes of convexity or concavity
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/04—Indexing scheme for image data processing or generation, in general involving 3D image data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20036—Morphological image processing
    • G06T2207/20044—Skeletonization; Medial axis transform
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G06T2207/20132—Image cropping
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30028—Colon; Small intestine
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30061—Lung
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30172—Centreline of tubular or elongated structure
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2210/00—Indexing scheme for image generation or computer graphics
    • G06T2210/41—Medical
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
    • G06T2219/028—Multiple view windows (top-side-front-sagittal-orthogonal)
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
    • G06T2219/20—Indexing scheme for editing of 3D models
    • G06T2219/2012—Colour editing, changing, or manipulating; Use of colour codes

Definitions

  • the present invention relates generally to computer-based three dimensional visualization and more particularly relates to improved methods for virtual navigation and examination including identifying regions which have been missed during navigation and electronic cleansing.
  • 3D imaging techniques for exploring virtual representations of objects.
  • medical image data can be transformed into a 3D virtual representation of an organ, such as the colon, to allow a thorough examination of the region.
  • the field of view available is generally directed only along the direction of navigation through the colon.
  • FIG. 1 because of the folded nature of the colon lumen, this can result in a substantial portion of the colon not being visible during optical colonoscopy.
  • the viewer can change navigation direction and can also orient the virtual camera in any direction. While this flexibility allows the radiologist or other viewer to explore the entire surface of the colon, it is often difficult or impossible for a viewer to know whether a particular region has been explored. Thus, improved navigational aids would be desirable.
  • the 3D virtual environment can also be used to perform quantifiable analysis, such as distance and volume measurements in a region of interest.
  • quantifiable analysis such as distance and volume measurements in a region of interest.
  • measurements generally involve the use of manually outlining a region for volume measurements.
  • 3D ray-surface intersection have been used to perform length, diameter and angular measurements. Such techniques tend to be time consuming or computationally expensive. Thus, improvements for performing quantitative measurements in a virtual environment are desired.
  • a method for enhancing virtual examination of an object provides for insuring that a virtual examination is thorough.
  • the method includes marking voxels in an image dataset as viewed when those voxels are presented on a user display as part of a rendered image. By marking viewed voxels, it is then possible to identify the unmarked voxels upon completion of an initial examination. Once the unviewed regions are identified, a user display identifying all regions of voxels identified which have a size larger than a predetermined threshold is provided.
  • the user display is a 2D planar projection of a 3D closed object.
  • a colon lumen can be “unraveled” into a 2D planar surface to exposes the entire inside surface of the colon.
  • the 2D planar projection can provide the display for a graphical user interface, which allows the user to select a region of unviewed voxels such that a display of the 3D closed object at the selected region is presented for examination.
  • a further method in accordance with the present invention provides for quantitative measurement of physical parameters of a virtual object.
  • This method includes placing at least one measuring disk at a location along a centerline of a virtual object.
  • the measuring disk is a fiducial marker which defines a plane that is aligned perpendicular to the centerline of the object.
  • diameter measurements can be taken.
  • a distance along the centerline and the volume of a region can be measured.
  • angular measurements can be performed.
  • Yet another method for enhancing a virtual examination includes electronically cleaning a virtual object.
  • This method includes defining a number of intensity value ranges which represent corresponding material type classifications in the image.
  • At least one set of intersection conditions which correspond to expected intersection regions are also defined. The intersection conditions are generally defined based on observed, repeatable characteristics of the intensity profile in the intersection regions. Boundary regions between at least a portion of the material type classifications are then identified in the image data. From the boundary regions, segmentation rays are cast towards neighboring voxels to detect regions which satisfy the defined intersection conditions. Once identified, intersection region specific correction is performed on the detected regions. Volumetric contrast enhancement can also be performed to further resolve any remaining partial volume effects.
  • Boundary regions can be identified by selecting a material type for segmentation; identifying seed voxels in the regions of the selected material type; and then applying region growing from the seed voxels until a boundary between the selected material type and another material type is detected.
  • the virtual object is a colon and the material type classifications include air, soft tissue, and fluid-stool-bone.
  • intersection regions include air-soft tissue, air-stool and air-fluid regions.
  • the intersection specific correction labels at least a portion of the voxels of the ray as colon wall and labels a portion of the voxels of the ray as mucosa.
  • the intersection specific correction labels voxels of the region as air voxels.
  • the intersection specific correction includes reconstructing the voxels in the region by labeling at least a portion of the stool voxels as fluid voxels and labeling a portion of the voxels of the ray as mucosa.
  • Also in accordance with the present invention is a method for coordinating the display of a 3D image and one or more corresponding 2D images.
  • This method includes displaying a 3D image of a region along with displaying a moveable slice marker on the 3D image.
  • a 2D image corresponding to the position and orientation of the slice marker is also displayed. If a different 2D image is selected, such as by manipulating a user interface, the marker position in the 3D image changes accordingly.
  • the 2D images are generally cross-sectional slices such as sagital, a coronal, axial or centerline-normal cross sectional images.
  • FIG. 1 is a pictorial view of a cross section of a colon lumen illustrating regions of visible surfaces during conventional optical colonoscopy;
  • FIG. 2 is a simplified block diagram of a method for determining regions missed during navigation
  • FIG. 3 is a pictorial diagram illustrating a planar representation of lumenal object mapped to a 2D plane to improve the visualization of missed regions of an object.
  • FIG. 4 is a pictorial view of a cross section of a colon lumen illustrating a virtual camera being brought to a selected “missed patch” for viewing.
  • FIG. 5 is a pictorial diagram illustrating an exemplary use of “measuring disks” for performing quantitative measurements in virtual visualization applications.
  • FIG. 6 is a pictorial diagram illustrating an exemplary use of measuring disks in order to determine the diameter of a region of interest
  • FIG. 7 is a pictorial diagram illustrating an exemplary use of measuring disks in order to determine the length of a region of interest
  • FIG. 8 is a pictorial diagram illustrating an exemplary use of measuring disks in order to determine the volume of a region of interest
  • FIG. 9 is a pictorial diagram illustrating an exemplary use of measuring disks in order to determine the angle of curvature of a region of interest
  • FIG. 10 is a graph which illustrates an exemplary intensity profile for CT image data of a colon
  • FIG. 11 is a flow chart which illustrates an overview of the present segmentation ray electronic segmentation process
  • FIG. 12 is a graph illustrating an intensity histogram of representative CT data of a colon
  • FIG. 13 is a graph illustrating an intensity profile at an intersection of air and soft tissue voxels within a colon
  • FIG. 14 is a graph illustrating the intensity profile of an intersection of air and fluid voxels within a colon
  • FIG. 15 is a graph illustrating the intensity profile of an intersection of air and stool voxels within a colon
  • FIG. 16 is a simplified 2D graphical representation of casting segmentation rays from boundary voxels to locate regions of intersection;
  • FIG. 17 is a graphical representation of the classification of voxels on a ray which detects an air-soft tissue intersection
  • FIG. 18 is a graphical representation of the classification of voxels on a ray which detects an air-fluid intersection
  • FIG. 19 is a graphical representation of the classification and reconstruction of voxels on a ray which detects an air-stool intersection
  • FIG. 20 is a graph illustrating an exemplary transfer function which can be used to map voxels from an original intensity to a reconstructed intensity during a volumetric contrast enhancement operation
  • FIG. 21 is a diagram illustrating the projection of image rays in normal perspective projection
  • FIG. 22 is a diagram illustrating the projection of image rays using equal angular spacing to increase the field of view.
  • FIG. 23 is a pictorial representation of an exemplary user interface for a virtual examination system illustrating the use of moving cross section marking.
  • a method for enhancing a virtual examination allows a user to quickly identify areas which have not been examined and to be brought to those areas in order to complete a full examination of a virtual object.
  • This process involves marking those areas which have been viewed during navigation (step 205 ) and using this marked data to identify those regions which have not been viewed (step 210 ). Once the unviewed regions have been identified, this information can be presented to the viewer in various forms. (Step 215 ).
  • the process of marking areas which have been viewed can be performed by storing, in computer readable media, an auxiliary volume buffer that is updated by marking those portions of the volume which are presented to the user on a display during image rendering of the main image data.
  • the marking process can be a binary marking process, designating voxels as viewed versus not viewed.
  • the marking of those regions which have been viewed can be a quantitative marking process which captures a measure of how the given voxel was used during the navigation. For example, a numeric value proportional to a particular voxels participation while being displayed can be stored.
  • the auxiliary volume is analyzed to identify voxels which have not been marked as viewed.
  • a region growing algorithm can be used to determine the boundaries of the “missed patch” in which the seed voxel belongs. This process is repeated until substantially all of the voxels which make up the surface of the object have been tagged as either viewed or as part of a missed patch.
  • the user can define a value in the marking range as the stop value for region growing.
  • the missed patch of continuously marked voxels can then be displayed as a gray scale or multi-color region which signifies the level of use of the voxels in the missed patch.
  • the object being examined such as a virtual colon
  • properties such as folds and curves, which make it difficult to observe certain areas of the object during normal navigation and examination.
  • mapping a 3D surface such as tube or sphere
  • Many of these techniques, such as Mercator, oblique, cylindrical and stereographic mapping have been used extensively in the field of map making, where surfaces of the globe must be represented on a planar map.
  • the 2D display while of value in enhancing the visibility of missed patches 305 , 310 , 315 , is not suitable for other purposes in visualization and examination. Instead, it is preferred that the 2D display provides the user with an effective way to visualize and select a missing patch 305 using a graphical user interface 325 . By selecting a particular missed patch, the system can then automatically bring the user to a display of the original 3D volume where the virtual camera is directed to the missed patch, as illustrated in FIG. 4 . As a user selects the missed patches and examines these regions, the region can be marked as viewed and removed from the 2D representation of missed patches on the object surface.
  • the missed patches can be identified in a list of coordinates or as a series of selectable bookmarks in tabular form.
  • the user can then sequentially view the designated regions or can manually select the various regions from the list of bookmarks. In either case, the user is presented with an indication of regions which were not viewed during initial examination thereby allowing the viewer to accomplish 100 percent viewing of the surface of interest.
  • 3D visualization it is desirable to not only view a region, but also to perform quantitative measurements in a region of interest.
  • An example of this can be found in the context of evaluating the aorta for abdominal aortic aneurysm (AAA) treatment.
  • AAA abdominal aortic aneurysm
  • the present invention uses a concept referred to as measuring disks to facilitate such quantitative measurements.
  • a measuring disk is a flat plane which intersects the surface of a virtual object as its travels along a centerline about the disk origin, while remaining perpendicular at the point of local centerline intersection.
  • An example of a number of measuring discs placed within a lumen is illustrated in FIG. 5 . While the use of a disk shape is preferred, it is not necessary. For example, any other shape which acts as a fiducial marker on the center line and projects perpendicularly therefrom can generally be used.
  • the radius of a measuring disk is adaptive in that it conforms to the dimensions of the structure in which it resides. Based on user preference, the disk can have a circular radius equal to the maximum interior radius of the lumen or the minimum interior radius of the lumen at each point along the centerline. In the event the minimum interior radius is preferred, the measuring disk will be fully contained within the virtual object with the possibility of small gaps occurring in places larger than this minimum. If the maximum radius is preferred, portions of the disk may extend through the surface of the object being examined.
  • a user will place one or more measuring disks along the centerline of the object at selected points of interest.
  • This is generally an interactive process which is performed using a graphical user interface, such as a computer mouse controlling a pointer on a computer display, to position the disks within the object which has been rendered translucent or transparent on the display.
  • the diameter of a lumen at a given point 600 can be determined by the placement of a single measuring disc 605 at this location.
  • length measurements can be simplified by placing a first measuring disk 705 at a first location of the lumen and a second disk 710 at a second location of the lumen.
  • the length along the segment of the centerline 715 between measuring disks 705 , 710 is determined and used as the actual length of the segment of interest. This provides accurate measurements of length for objects which may be tortuous, such as regions of the colon and aorta.
  • the volume of a region can also be determined using two measuring disks.
  • a volume is contained by the boundary 805 of the region of interest and measuring disks 805 , 810 .
  • the volume can be determined in this captured region can be determined by counting the number of voxels contained in the captured region and multiplying this number by the equivalent volume of a single voxel.
  • FIG. 9 illustrates the use of three measuring disks to determine of angle of curvature of an object of interest.
  • the three disks define two endpoints 905 , 910 and the vertex of an inner angle and an outer angle.
  • the disks can be positioned independently along the lumen to variably define the endpoints and vertex of interest.
  • the angle can be defined as an inner angle, which is defined by the intersection of rays 920 , 925 which join the origins of the disks 905 , 915 and 910 , 915 .
  • the angle can also be defined as an outer angle.
  • rays 930 , 935 is projected from the origin of each end point disk 905 , 910 along a tangent of the centerline towards the vertex.
  • the origins of the three measuring disks are used to define a common plane on which to project the rays. In this way, the rays projected from the endpoints are guaranteed to converge.
  • colonic fluid and stool within the colon may mask polyps if not removed.
  • removal of such stool and fluid requires significant pre-imaging protocols which require the ingestion of large quantities of fluids and contrast agents and pre-imaging enema's to complete colonic cleansing.
  • electronic cleansing techniques such as image segmentation, can be used to effectively clean a virtual object.
  • the present invention introduces an improved method for segmentation and digital cleansing of a virtual object, such as a colon, which provides effective treatment for areas which exhibit a partial volume effect which prevents removal by traditional segmentation.
  • FIG. 10 is a graph which illustrates an exemplary intensity profile for CT image data of a colon.
  • This intensity graph there are three distinct plateau levels signifying soft tissue 1005 , air 1010 and fluid voxels 1015 .
  • the high intensity of the fluid is the result of ingestion of a contrast agent prior to imaging. While these regions are readily distinguishable using traditional image segmentation techniques, the sloped parts of the graph which represent the interface of these regions are difficult to classify.
  • These voxels are considered partial volume effect (PVE) voxels 1020 since the intensity is effected by a mix of voxels of the two regions forming the intersection.
  • PVE voxels are difficult to classify using segmentation, the boundary between regions is often distorted and may not accurately reflect the region of interest. For example, alliasing effects of segmentation may result in abrupt borders which remove intermediate layers of material such as colonic mucosa. However, such intermediate regions may be valuable diagnostic aids and should be preserved in the segmented image.
  • the present invention introduces the notion of segmentation rays which are projected from boundary voxels to identify regions of intersection using predetermined intersection characteristics. When a region of intersection is identified, intersection specific adjustments are performed to resolve ambiguities resulting from the partial volume effect.
  • FIG. 11 is a flow chart which illustrates an overview of the present segmentation ray electronic segmentation process.
  • the image data is classified into a predetermined number of categories or bins based on expected intensity value.
  • regions designated as air (AIR) 1205 , soft tissue (ST) 1210 and fluid, stool, bone (FSB) 1215 can be defined by ranges of intensity values.
  • regions of partial volume effect such as PV 1 1220 and PV 2 1225 .
  • the classifications are generally assigned by the system or the user based on prior knowledge of the object being imaged and the expected intensity values for the material being imaged.
  • the unique intensity profiles for the different intersections between regions are studied to determine a set of characteristics which can be stored for later use.
  • seed points are located in those regions which are to be segmented.
  • seed points are located in those regions which are to be segmented.
  • an effective technique is to identify a voxel which has an intensity in the FSB intensity region and then examine those voxels located directly above it. If an FSB voxel has an AIR voxel immediately above it, that AIR voxel is within the colon and can be stored as a seed voxel. This condition results from the fact that gravity forces the fluid to collect in the lower portions of the colonic folds and establish a smooth horizontal interface surface with the air which is within the colon. For FSB voxels outside the colon, such as bone, these voxels will be bordered by soft tissue, not air voxels, and the described condition will not be satisfied.
  • the process of detecting the seed voxels can be implemented by traversing each vertical scan-line in the image data to determine if the condition, i.e., AIR above FSB, is satisfied. If so, the AIR voxel is stored as a seed point in a suitable data structure, such as an array. When the seed point detection evaluation is complete, region growing can be used from each seed to determine the boundary between AIR and other regions. (Step 1115 ).
  • Region growing can be performed using a naive dilate-and growing strategy. This process can be made more efficient by maintaining a data structure for those voxels whose neighbors have not been analyzed.
  • a first seed voxel is removed from the data structure and its neighbors are inspected. If a non-masked AIR voxel is found, this voxel is stored. If a masked AIR voxel is detected, this voxel is ignored. If a non-AIR voxel is found, this voxel is marked as a boundary voxel and is stored in a separate data structure (BV queue).
  • BV queue separate data structure
  • the voxel is masked to indicate that it has been processed. This process is repeated for all seed voxels.
  • a 6-connection analysis (six neighbors evaluated) can be used. However, for evaluating boundary conditions a 26-connection (26 neighbors about the current voxel) is preferred to improve accuracy.
  • segmentation rays can be cast to determine areas which satisfy predetermined sets of intersection criteria which indicate various corresponding regions of intersection (step 1120 ).
  • This step involves prior evaluation of the intensity profiles at exemplary regions of intersection and isolating a set of characteristics which differentiate the respective intersection regions. An example of this process will be described in the context of the expected intersection regions of the colon. It will be appreciated, that the particular sets of intersection characteristics are application specific and will depend on a number of variables, such as the materials being imaged.
  • the AIR regions within a colon are identified and boundaries of intersection between AIR and other regions determined. These intersections will represent either an AIR-ST intersection, and AIR-fluid intersection, or an AIR-stool intersection. By characterizing these intersections using unique properties observed in the intensity profiles of such regions of intersection, specific corrections can be applied to remove the partial volume effect.
  • FIG. 13 is a graph illustrating an intensity profile at an AIR-ST intersection.
  • This profile is characterized by: a gradual increase in the gradient as intensities transition from air, through PV 1 , to the soft tissue intensity and, possibly, to the PV 2 region 1310 as well; after the first negative or zero gradient 1305 , the intensity value remains in the ST range, the intensities do not enter the FSB region; and no more than one PV 2 region voxel 1310 is present before a negative or zero gradient.
  • FIG. 14 is a graph illustrating the intensity profile of an AIR-fluid intersection region. This intersection is characterized by: a sharp rise in the gradient as the intensity values move from air to FSB; the presence of three or less PV 1 voxels encountered between the AIR and FSB regions; and the voxels following the first negative gradient remain in the FSB intensity range.
  • FIG. 15 is a graph illustrating the intensity profile of an AIR-stool intersection. This intersection is characterized by: a sharp rise in the gradient as the intensity values move from air to PV 2 or FSB; and after the first negative gradient, the intensity values are in the PV 2 region.
  • intersection detection requires testing the cast segmentation rays to determine if any of the sets of intersection conditions are met.
  • Ray casting is performed at each of the identified boundary voxels. The rays are cast outwards in a direction to each of the 26-connected neighbors which are not the same type as the seed voxel (in this case, all neighbors which are not AIR voxels).
  • a simplified 2D representation of the ray casting of step 1120 is illustrated in pictorial form in FIG. 16 . In FIG. 16 , the boundary voxels are marked B and the AIR voxels are marked A.
  • segmentation rays are extended, they are tested to determine if one of the sets of intersection conditions are met. If one of the predetermined sets of intersection conditions are met, a respective correction process, described below, can be applied. If no set of intersection conditions are satisfied within a predetermined ray distance, that ray is dropped.
  • intersection correction processes are predetermined to correct for the expected errors introduced by the partial volume effect.
  • the last two voxels of the ray are designated as colon wall voxels and the remaining voxels on the ray are marked as mucosa voxels. While this is not intended to accurately distinguish between colon wall and mucosa, the inner contour of the colon wall which will show any polyps is accurately preserved.
  • these voxels are removed by assigning the voxels an intensity in the AIR region. This operation continues the process of removing fluid voxels from the colon interior.
  • the objective is to remove the stool voxels while preserving and correcting the position of the underlying mucosa voxels. This can be accomplished by moving the stool voxels along the ray and moving the mucosa voxels into their correct position as shown in the graph of FIG. 19 .
  • volumetric contrast enhancement of step 1130 can then be applied to correct these last conditions.
  • the volumetric contrast enhancement applies the transfer function illustrated in the graph of FIG. 20 to increase the contrast between the ST region and the FSB region which is to be removed.
  • the voxels in the Fluid-ST intersection close to the ST intensity are moved into the ST region and are maintained whereas the voxels in the intersection closer to the FSB region or are moved into the FSB region for removal.
  • the graph of FIG. 20 while preferred, is but one example of a transfer function which can be used to effect the desired contrast enhancement and it will be appreciated that other curves, even a straight line having a predetermined slope, can also be employed.
  • a perspective mapping is used to project 3D voxels onto the 2D image plane of the computer display.
  • perspective projection results in rays from a limited field of view being projected from the source into equally spaced positions on the image surface. This results in a minimally distorted image which closely resembles that which would be observed by a conventional camera.
  • it would be desirable to provide a user with a wider field of view i.e., >60 degrees.
  • the field of view widens, the image tends to become distorted. Further, a field of view of 180 degrees cannot be achieved with normal perspective projection.
  • the present application of equidistant fish eye projection can be used in virtual examinations to provide an increased field of view which retains critical features, such as the spherical nature of polyps being examined in virtual colonoscopy.
  • the objective is to project the image rays along an equal angular spacing from the origin.
  • a voxel (x,y,z) onto the image plane is performed by computing two angles ( ⁇ , ⁇ ) relative to the forward viewing direction and the right vector respectively.
  • a ray is computed by then rotating the view forward ray about the view up direction by ⁇ and then rotating again by ⁇ about the view forward direction.
  • the resulting ray is then cast through volume in the similar manner to the usual volume rendering process.
  • the preceding computations can be made more efficient by pre-computing the two angles ( ⁇ , ⁇ ) for the entire image or even the corresponding rotation matrices.
  • the present methods can be integrated as improvements to known systems and methods for performing 3D visualization, navigation and examination. Such systems and methods are described, for example, in U.S. Pat. No. 5,971,767 to Kaufman et al. entitled “System and Method for Performing a Virtual Examination,” which is hereby incorporated by reference in its entirety.
  • the present methods can be performed on any number of computer processing platforms, including personal computer systems. For example, an IBM compatible Wintel PC operating under the Windows2000 operating system and having a single 1 GHZ CPU is generally suitable for such applications.
  • an additional improvement with respect to virtual navigation and examination is the ability to navigate in a 3D environment while being able to cross-reference the current navigation to one or more 2D images.
  • the present invention provides for the display of markers in a 3D environment and the concurrent display of one or more 2D images corresponding to the marker position.
  • slice marker 2210 corresponds to the sagital cross sectional image 2215
  • slice marker 2220 corresponds to the coronal cross sectional image 2225
  • slice marker 2230 corresponds to the axial cross sectional image 2235 .
  • the axial, coronal and sagital images are reformatted 2D images which are aligned with the axes of the patient.
  • slice marker 2240 corresponds to cross sectional image 2245 which is aligned perpendicularly to the centerline of the object. This view is referred to as a centerline-normal cross section.
  • each reformatted cross sectional image has an associated scroll bar 2250 .
  • This provides a graphical user interface for positioning the respective marker to a region of interest in the 3D image, and vice versa, such that the 2D image and 3D image can synchronously display a selected region of interest.
  • the scroll bar, or other user interface As the scroll bar, or other user interface, is moved, the 2D image changes to display the reformatted 2D image at the newly selected position.
  • the marker in the 3D position is moved to reflect the selected cross sectional image which is being currently being displayed.
  • visual coordination is achieved among disparate views and viewing modes.
  • each cross sectional window has a navigation marker 2255 which corresponds to the current navigation position and viewing direction in the 3D object.
  • FIG. 23 While in FIG. 23 four different cross sectional images, and associated slice markers, are shown, it is preferred that each of these images can be selected or deselected by the user. Generally, only one cross sectional image will be selected by a user during any given operation.
  • the slice markers 2210 , 2220 , 2230 , 2240 are preferably displayed with a color or translucency which allows them to be differentiated in the 3D display without obscuring the content of the 3D image window.
  • a color or translucency which allows them to be differentiated in the 3D display without obscuring the content of the 3D image window.
  • Coloration of the slice markers can be achieved by modifying the base voxel color within the volume rendering module.
  • volume rendering the distance from each 2D slice plane of each visible voxel is computed. This is performed by direct computation of the plane equation for each voxel of each plane.
  • A,B,C and D are the plane equation coefficients which define the 2D slice location in three dimensions.
  • the current voxel location is given by (x,y,z).
  • Voxels precisely on the plane have a distance value equal to zero, while voxels at some distance from the plane have a non-zero value proportional to the distance from the plane, when the coefficients are pre-normalized.
  • computing the plane equation for a voxel results in that voxel's distance from the plane.
  • a voxel is considered part of the plane when the absolute value of the distance from the plane is less than a predetermined threshold value. If the voxel is considered within the plane, the base color will be modified during volume rendering.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Graphics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Geometry (AREA)
  • Software Systems (AREA)
  • Computer Hardware Design (AREA)
  • General Engineering & Computer Science (AREA)
  • Architecture (AREA)
  • Image Generation (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
  • Processing Or Creating Images (AREA)
  • Image Analysis (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Endoscopes (AREA)
  • Ultra Sonic Daignosis Equipment (AREA)
  • Image Processing (AREA)
US10/380,210 2000-10-02 2001-10-02 Enhanced virtual navigation and examination Expired - Fee Related US7706600B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US10/380,210 US7706600B2 (en) 2000-10-02 2001-10-02 Enhanced virtual navigation and examination

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US23731100P 2000-10-02 2000-10-02
US10/380,210 US7706600B2 (en) 2000-10-02 2001-10-02 Enhanced virtual navigation and examination
PCT/US2001/030942 WO2002029723A1 (fr) 2000-10-02 2001-10-02 Navigation et examen virtuels ameliores

Publications (2)

Publication Number Publication Date
US20070003131A1 US20070003131A1 (en) 2007-01-04
US7706600B2 true US7706600B2 (en) 2010-04-27

Family

ID=22893204

Family Applications (2)

Application Number Title Priority Date Filing Date
US10/380,211 Expired - Fee Related US7574024B2 (en) 2000-10-02 2001-10-02 Centerline and tree branch skeleton determination for virtual objects
US10/380,210 Expired - Fee Related US7706600B2 (en) 2000-10-02 2001-10-02 Enhanced virtual navigation and examination

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US10/380,211 Expired - Fee Related US7574024B2 (en) 2000-10-02 2001-10-02 Centerline and tree branch skeleton determination for virtual objects

Country Status (5)

Country Link
US (2) US7574024B2 (fr)
EP (2) EP1402478A4 (fr)
JP (5) JP2004522464A (fr)
AU (2) AU2001296506A1 (fr)
WO (2) WO2002029723A1 (fr)

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090052760A1 (en) * 2002-07-08 2009-02-26 Vision Rt Limited Image processing system for use with a patient positioning device
US20100201786A1 (en) * 2006-05-11 2010-08-12 Koninklijke Philips Electronics N.V. Method and apparatus for reconstructing an image
US20100208956A1 (en) * 2005-11-30 2010-08-19 The Research Foundation Of State University Of New York Electronic colon cleansing method for virtual colonoscopy
US20110242097A1 (en) * 2010-03-31 2011-10-06 Fujifilm Corporation Projection image generation method, apparatus, and program
US20110255763A1 (en) * 2010-04-15 2011-10-20 Siemens Medical Solutions Usa, Inc. Enhanced Visualization of Medical Image Data
TWI419080B (zh) * 2010-12-07 2013-12-11 私立中原大學 用於室內設計色彩調和系統之方法
US8641210B2 (en) 2011-11-30 2014-02-04 Izi Medical Products Retro-reflective marker including colored mounting portion
US8661573B2 (en) 2012-02-29 2014-03-04 Izi Medical Products Protective cover for medical device having adhesive mechanism
US9498290B2 (en) 2012-07-19 2016-11-22 MRI Interventions, Inc. Surgical navigation devices and methods
US20170305013A1 (en) * 2016-04-25 2017-10-26 Disney Enterprises, Inc. Map localizing with partially obstructed ranging devices for autonomous robots and vehicles
USD824027S1 (en) 2016-01-13 2018-07-24 MRI Interventions, Inc. Fins for a support column for a surgical trajectory frame
USD829904S1 (en) 2016-01-13 2018-10-02 MRI Interventions, Inc. Curved bracket for surgical navigation systems
US10376333B2 (en) 2016-01-14 2019-08-13 MRI Interventions, Inc. Devices for surgical navigation systems

Families Citing this family (100)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7324104B1 (en) * 2001-09-14 2008-01-29 The Research Foundation Of State University Of New York Method of centerline generation in virtual objects
ATE314703T1 (de) * 2001-10-16 2006-01-15 Koninkl Philips Electronics Nv Verfahren zur automatischen etikettierung von zweigen
JP2003141548A (ja) * 2001-10-22 2003-05-16 Ge Medical Systems Global Technology Co Llc ３次元ラベリング装置及びその方法
US20030132936A1 (en) * 2001-11-21 2003-07-17 Kevin Kreeger Display of two-dimensional and three-dimensional views during virtual examination
JP4564233B2 (ja) * 2003-01-31 2010-10-20 株式会社東芝 画像処理装置、画像データ処理方法、及びプログラム
US7333644B2 (en) 2003-03-11 2008-02-19 Siemens Medical Solutions Usa, Inc. Systems and methods for providing automatic 3D lesion segmentation and measurements
US7304644B2 (en) * 2003-03-12 2007-12-04 Siemens Medical Solutions Usa, Inc. System and method for performing a virtual endoscopy
US7457444B2 (en) 2003-05-14 2008-11-25 Siemens Medical Solutions Usa, Inc. Method and apparatus for fast automatic centerline extraction for virtual endoscopy
US7489810B2 (en) * 2003-06-06 2009-02-10 Ge Medical Systems Information Technologies, Inc. Method and system for linking location information between software applications for viewing diagnostic medical images
US7349563B2 (en) * 2003-06-25 2008-03-25 Siemens Medical Solutions Usa, Inc. System and method for polyp visualization
US7613316B2 (en) * 2003-07-22 2009-11-03 L-3 Communications Security and Detection Systems Inc. Methods and apparatus for detecting objects in baggage
US7300398B2 (en) * 2003-08-14 2007-11-27 Siemens Medical Solutions Usa, Inc. Method and apparatus for registration of virtual endoscopic images
US7574032B2 (en) * 2003-10-31 2009-08-11 General Electric Company Method and apparatus for virtual subtraction of stool from registration and shape based analysis of prone and supine scans of the colon
JP2007537770A (ja) * 2003-11-03 2007-12-27 ブラッコ イメージング エス．ピー．エー． 内視鏡画像内の管腔状構造のディスプレイ最適化のための動的なクロップボックス決定方法
CN1902640A (zh) * 2003-11-12 2007-01-24 西门子共同研究公司 对医学图像中的候选解剖结构进行滤波和自动检测的系统和方法
US7310435B2 (en) * 2003-11-25 2007-12-18 General Electric Company Method and apparatus for extracting multi-dimensional structures using dynamic constraints
US20050256400A1 (en) * 2003-12-03 2005-11-17 Bhargav Raman Method to identify arterial and venous vessels
US7609887B2 (en) * 2004-06-07 2009-10-27 Siemens Medical Solutions Usa, Inc. System and method for toboggan-based object segmentation using distance transform
JP3943563B2 (ja) * 2004-08-11 2007-07-11 ザイオソフト株式会社 画像表示方法及び画像表示プログラム
JP2008521461A (ja) * 2004-11-26 2008-06-26 ブラッコ イメージング ソチエタ ペル アチオニ 知識構造のマッピングを使用した管状器官を測定する方法
JP4146438B2 (ja) * 2005-01-19 2008-09-10 ザイオソフト株式会社 識別方法
US8712115B2 (en) * 2005-04-19 2014-04-29 Siemens Medical Solutions Usa, Inc. Real-time virtual endoscopy
US20060258935A1 (en) * 2005-05-12 2006-11-16 John Pile-Spellman System for autonomous robotic navigation
US9492240B2 (en) 2009-06-16 2016-11-15 Intuitive Surgical Operations, Inc. Virtual measurement tool for minimally invasive surgery
US8971597B2 (en) 2005-05-16 2015-03-03 Intuitive Surgical Operations, Inc. Efficient vision and kinematic data fusion for robotic surgical instruments and other applications
US7889897B2 (en) * 2005-05-26 2011-02-15 Siemens Medical Solutions Usa, Inc. Method and system for displaying unseen areas in guided two dimensional colon screening
US7379062B2 (en) * 2005-08-01 2008-05-27 Barco Nv Method for determining a path along a biological object with a lumen
EP1913554A2 (fr) * 2005-08-01 2008-04-23 Koninklijke Philips Electronics N.V. Procede et appareil de mise en correspondance de deux images numeriques d'un objet
US7903851B2 (en) * 2005-10-17 2011-03-08 Siemens Medical Solutions Usa, Inc. Method and system for vertebrae and intervertebral disc localization in magnetic resonance images
US7711168B2 (en) * 2005-10-19 2010-05-04 Siemens Medical Solutions Usa, Inc. Method for tracking blood vessels
US8548566B2 (en) * 2005-10-21 2013-10-01 Koninklijke Philips N.V. Rendering method and apparatus
US20070109299A1 (en) * 2005-11-15 2007-05-17 Vital Images, Inc. Surface-based characteristic path generation
JP4808477B2 (ja) * 2005-11-25 2011-11-02 ザイオソフト株式会社 画像処理方法及び画像処理プログラム
WO2007064981A2 (fr) * 2005-11-30 2007-06-07 The Research Foundation Of State University Of New York Systeme et procede de reduction de faux positifs pendant la detection de polypes assistee par ordinateur
DE102006003179B4 (de) * 2006-01-23 2009-02-26 Siemens Ag Verfahren und Vorrichtung zur virtuellen Endoskopie eines Hohlkanals
US8023703B2 (en) * 2006-07-06 2011-09-20 The United States of America as represented by the Secretary of the Department of Health and Human Services, National Institues of Health Hybrid segmentation of anatomical structure
US7929741B2 (en) * 2006-08-14 2011-04-19 Siemens Medical Solutions Usa, Inc. System and method for automated detection of mucus plugs within bronchial tree in MSCT images
US8014561B2 (en) * 2006-09-07 2011-09-06 University Of Louisville Research Foundation, Inc. Virtual fly over of complex tubular anatomical structures
US7786990B2 (en) 2006-11-22 2010-08-31 Agfa Healthcare Inc. Cursor mode display system and method
WO2008089490A2 (fr) * 2007-01-19 2008-07-24 Mayo Foundation For Medical Education And Research Affichage suivant une ligne médiane axiale d'images de colonographie générées par tomographie assistée par ordinateur
US8564593B2 (en) * 2007-01-19 2013-10-22 Mayo Foundation For Medical Education And Research Electronic stool subtraction using quadratic regression and intelligent morphology
US8442290B2 (en) 2007-01-19 2013-05-14 Mayo Foundation For Medical Education And Research Simultaneous dual window/level settings for display of CT colonography images
US9014439B2 (en) * 2007-01-19 2015-04-21 Mayo Foundation For Medical Education And Research Oblique centerline following display of CT colonography images
WO2008091583A2 (fr) * 2007-01-23 2008-07-31 Dtherapeutics, Llc Extraction fondée sur des images pour l'obtention d'une cartographie de l'arbre vasculaire
CN100583164C (zh) * 2007-01-24 2010-01-20 中国科学院自动化研究所 一种树状形体的立体分解和分级骨架提取方法
ATE544132T1 (de) 2007-05-30 2012-02-15 Cleveland Clinic Foundation Automatisiertes mittellinien-extraktionsverfahren und erzeugung eines entsprechenden analytischen ausdrucks und verwendung hierfür
DE102007028065A1 (de) * 2007-06-19 2009-01-02 Siemens Ag Vorrichtung und Verfahren zur automatischen Wegplanung
US8339418B1 (en) * 2007-06-25 2012-12-25 Pacific Arts Corporation Embedding a real time video into a virtual environment
JP5114121B2 (ja) * 2007-07-18 2013-01-09 株式会社日立メディコ 医用画像処理装置
CN101836235A (zh) * 2007-08-16 2010-09-15 皇家飞利浦电子股份有限公司 用于对三维(3d)图像数据体积中的横截平面进行采样的成像方法
WO2009071106A1 (fr) * 2007-12-05 2009-06-11 MAX-PLANCK-Gesellschaft zur Förderung der Wissenschaften e.V. Procédé d'analyse d'image, système d'analyse d'image et leurs utilisations
JP2012510317A (ja) 2008-11-28 2012-05-10 フジフイルム メディカル システムズ ユーエスエイ インコーポレイテッド 脊椎のラベル付けの伝搬のためのシステムおよび方法
JP5572555B2 (ja) * 2008-12-25 2014-08-13 株式会社日立メディコ 医用画像表示装置及び方法
US8830224B2 (en) 2008-12-31 2014-09-09 Intuitive Surgical Operations, Inc. Efficient 3-D telestration for local robotic proctoring
WO2010113097A1 (fr) * 2009-04-03 2010-10-07 Koninklijke Philips Electronics N.V. Association d'une position de capteur à une position d'image
JP5302761B2 (ja) * 2009-04-30 2013-10-02 日立アロカメディカル株式会社 超音波診断装置
US9155592B2 (en) * 2009-06-16 2015-10-13 Intuitive Surgical Operations, Inc. Virtual measurement tool for minimally invasive surgery
DE102009033452B4 (de) * 2009-07-16 2011-06-30 Siemens Aktiengesellschaft, 80333 Verfahren zur Bereitstellung eines segmentierten Volumendatensatzes für eine virtuelle Koloskopie sowie zugehörige Gegenstände
US8275547B2 (en) * 2009-09-30 2012-09-25 Utility Risk Management Corporation, Llc Method and system for locating a stem of a target tree
EP2490602B1 (fr) 2009-10-21 2019-01-16 Koninklijke Philips N.V. Détermination interactive de paramètres d'enroulement
WO2011059655A1 (fr) * 2009-10-29 2011-05-19 Optovue, Inc. Imagerie améliorée pour tomographie par cohérence optique
US8819591B2 (en) * 2009-10-30 2014-08-26 Accuray Incorporated Treatment planning in a virtual environment
EP2504812B1 (fr) * 2009-11-27 2019-08-07 Cadens Medical Imaging Inc. Procédé et système de filtrage de données d'image et utilisation de ceux-ci dans une endoscopie virtuelle
US8666920B2 (en) * 2010-02-15 2014-03-04 Microsoft Corporation Estimating shortest distances in graphs using sketches
MY152058A (en) * 2010-06-21 2014-08-15 Univ Putra Malaysia A method of constructing at least one 3 dimensional image
JP5574852B2 (ja) * 2010-06-30 2014-08-20 キヤノン株式会社 情報処理装置、情報処理方法、システム及びプログラム
EP2619729B1 (fr) * 2010-09-20 2018-07-04 Koninklijke Philips N.V. Quantification d'une caractéristique d'une lumière d'une structure tubulaire
US8463011B2 (en) * 2010-09-30 2013-06-11 Siemens Aktiengesellschaft Tools for automatic colonic centerline extraction
US8922546B2 (en) * 2010-09-30 2014-12-30 Siemens Aktiengesellschaft Dynamic graphical user interfaces for medical workstations
WO2012092554A1 (fr) 2010-12-30 2012-07-05 Utility Risk Management Corporation, Llc Procédé pour localiser une végétation ayant un potentiel à impacter une structure
JP6013037B2 (ja) * 2011-06-23 2016-10-25 東芝メディカルシステムズ株式会社 医用画像処理装置
US8605973B2 (en) * 2012-03-17 2013-12-10 Sony Corporation Graph cuts-based interactive segmentation of teeth in 3-D CT volumetric data
CN102663700B (zh) * 2012-04-13 2014-11-05 福州大学 粘连颗粒二值图像的分割方法
US9153049B2 (en) 2012-08-24 2015-10-06 International Business Machines Corporation Resource provisioning using predictive modeling in a networked computing environment
JP5957409B2 (ja) * 2013-03-29 2016-07-27 富士フイルム株式会社 領域抽出装置および方法並びにプログラム
US9836879B2 (en) * 2013-04-16 2017-12-05 Autodesk, Inc. Mesh skinning technique
US9734616B1 (en) * 2013-10-11 2017-08-15 Pixar Tetrahedral volumes from segmented bounding boxes of a subdivision
US9754398B1 (en) * 2014-03-24 2017-09-05 Amazon Technologies, Inc. Animation curve reduction for mobile application user interface objects
USD784392S1 (en) * 2014-07-17 2017-04-18 Coretech System Co., Ltd. Display screen with an animated graphical user interface
US10242488B1 (en) * 2015-03-02 2019-03-26 Kentucky Imaging Technologies, LLC One-sided transparency: a novel visualization for tubular objects
JP5943287B2 (ja) * 2015-04-02 2016-07-05 国立大学法人名古屋大学 全球型視野をもつ仮想内視鏡装置
US9892506B2 (en) * 2015-05-28 2018-02-13 The Florida International University Board Of Trustees Systems and methods for shape analysis using landmark-driven quasiconformal mapping
US10304236B2 (en) * 2017-03-13 2019-05-28 Siemens Healthcare Gmbh Methods and systems for segmented volume rendering
US10169874B2 (en) * 2017-05-30 2019-01-01 International Business Machines Corporation Surface-based object identification
US10751621B2 (en) * 2017-09-01 2020-08-25 Square Enix Limited Method and system for rendering video game images
WO2019152850A1 (fr) 2018-02-02 2019-08-08 Centerline Biomedical, Inc. Segmentation de structures anatomiques
US11373330B2 (en) * 2018-03-27 2022-06-28 Siemens Healthcare Gmbh Image-based guidance for device path planning based on penalty function values and distances between ROI centerline and backprojected instrument centerline
CN109658426B (zh) * 2018-12-14 2021-10-29 上海联影医疗科技股份有限公司 结肠中心线修正方法、装置、设备和存储介质
GB201903154D0 (en) * 2019-03-08 2019-04-24 Congenita Ltd System and method for producing a tissue patch for use in reconstruction of tubular anatomical structures
US11151789B1 (en) 2019-03-25 2021-10-19 Kentucky Imaging Technologies Fly-in visualization for virtual colonoscopy
US11521316B1 (en) 2019-04-03 2022-12-06 Kentucky Imaging Technologies Automatic extraction of interdental gingiva regions
US11044400B1 (en) 2019-04-03 2021-06-22 Kentucky Imaging Technologies Frame stitching in human oral cavity environment using intraoral camera
CA3131069A1 (fr) 2019-04-04 2020-10-08 Centerline Biomedical, Inc. Modelisation de regions d'interet d'une structure anatomique
US11423318B2 (en) 2019-07-16 2022-08-23 DOCBOT, Inc. System and methods for aggregating features in video frames to improve accuracy of AI detection algorithms
US10671934B1 (en) 2019-07-16 2020-06-02 DOCBOT, Inc. Real-time deployment of machine learning systems
US11191423B1 (en) * 2020-07-16 2021-12-07 DOCBOT, Inc. Endoscopic system and methods having real-time medical imaging
US11771505B2 (en) * 2019-12-31 2023-10-03 Biosense Webster (Israel) Ltd. Three dimensional mapping system for cranial surgical pathways and method
JP6832479B1 (ja) * 2020-04-10 2021-02-24 株式会社ヴォクシス 立体を形状の狭隘部で分割する画像処理方法、画像処理プログラム、及び画像処理装置
US11100373B1 (en) 2020-11-02 2021-08-24 DOCBOT, Inc. Autonomous and continuously self-improving learning system
EP4012662A1 (fr) * 2020-12-09 2022-06-15 Koninklijke Philips N.V. Procédé d'identification de limite de matériau dans des données d'images volumétriques

Citations (61)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4367216A (en) 1979-06-28 1983-01-04 Schering Aktiengesellschaft Triiodinated 5-aminoisophthalic acid derivatives
US4391280A (en) 1980-04-04 1983-07-05 Miller Roscoe E Enema apparata improvements relating to double contrast studies
US4630203A (en) 1983-12-27 1986-12-16 Thomas Szirtes Contour radiography: a system for determining 3-dimensional contours of an object from its 2-dimensional images
US4710876A (en) 1985-06-05 1987-12-01 General Electric Company System and method for the display of surface structures contained within the interior region of a solid body
US4719585A (en) 1985-08-28 1988-01-12 General Electric Company Dividing cubes system and method for the display of surface structures contained within the interior region of a solid body
US4729098A (en) 1985-06-05 1988-03-01 General Electric Company System and method employing nonlinear interpolation for the display of surface structures contained within the interior region of a solid body
US4737921A (en) 1985-06-03 1988-04-12 Dynamic Digital Displays, Inc. Three dimensional medical image display system
US4751643A (en) 1986-08-04 1988-06-14 General Electric Company Method and apparatus for determining connected substructures within a body
US4791567A (en) 1986-09-15 1988-12-13 General Electric Company Three dimensional connectivity system employing an equivalence schema for determining connected substructures within a body
US4823129A (en) 1987-02-24 1989-04-18 Bison Instruments, Inc. Analog-to-digital converter
US4831528A (en) 1987-11-09 1989-05-16 General Electric Company Apparatus and method for improvement of 3D images derived from tomographic data
US4874362A (en) 1986-03-27 1989-10-17 Wiest Peter P Method and device for insufflating gas
US4879668A (en) 1986-12-19 1989-11-07 General Electric Company Method of displaying internal surfaces of three-dimensional medical images
US4984157A (en) 1988-09-21 1991-01-08 General Electric Company System and method for displaying oblique planar cross sections of a solid body using tri-linear interpolation to determine pixel position dataes
US4985834A (en) 1988-11-22 1991-01-15 General Electric Company System and method employing pipelined parallel circuit architecture for displaying surface structures of the interior region of a solid body
US4985856A (en) 1988-11-10 1991-01-15 The Research Foundation Of State University Of New York Method and apparatus for storing, accessing, and processing voxel-based data
US4987554A (en) 1988-08-24 1991-01-22 The Research Foundation Of State University Of New York Method of converting continuous three-dimensional geometrical representations of polygonal objects into discrete three-dimensional voxel-based representations thereof within a three-dimensional voxel-based system
US4993415A (en) 1988-08-19 1991-02-19 Alliance Pharmaceutical Corp. Magnetic resonance imaging with perfluorocarbon hydrides
US5006109A (en) 1989-09-12 1991-04-09 Donald D. Douglas Method and device for controlling pressure, volumetric flow rate and temperature during gas insuffication procedures
US5023072A (en) 1988-08-10 1991-06-11 University Of New Mexico Paramagnetic/superparamagnetic/ferromagnetic sucrose sulfate compositions for magnetic resonance imaging of the gastrointestinal tract
US5038302A (en) 1988-07-26 1991-08-06 The Research Foundation Of State University Of New York Method of converting continuous three-dimensional geometrical representations into discrete three-dimensional voxel-based representations within a three-dimensional voxel-based system
US5047772A (en) 1990-06-04 1991-09-10 General Electric Company Digital error correction system for subranging analog-to-digital converters
US5056020A (en) 1988-09-16 1991-10-08 General Electric Cge Sa Method and system for the correction of image defects of a scanner due to the movements of the latter
US5095521A (en) 1987-04-03 1992-03-10 General Electric Cgr S.A. Method for the computing and imaging of views of an object
US5101475A (en) 1989-04-17 1992-03-31 The Research Foundation Of State University Of New York Method and apparatus for generating arbitrary projections of three-dimensional voxel-based data
US5127037A (en) 1990-08-15 1992-06-30 Bynum David K Apparatus for forming a three-dimensional reproduction of an object from laminations
US5166876A (en) 1991-01-16 1992-11-24 General Electric Company System and method for detecting internal structures contained within the interior region of a solid object
US5170347A (en) 1987-11-27 1992-12-08 Picker International, Inc. System to reformat images for three-dimensional display using unique spatial encoding and non-planar bisectioning
US5187658A (en) 1990-01-17 1993-02-16 General Electric Company System and method for segmenting internal structures contained within the interior region of a solid object
US5204625A (en) 1990-12-20 1993-04-20 General Electric Company Segmentation of stationary and vascular surfaces in magnetic resonance imaging
US5229935A (en) 1989-07-31 1993-07-20 Kabushiki Kaisha Toshiba 3-dimensional image display apparatus capable of displaying a 3-D image by manipulating a positioning encoder
US5245538A (en) 1987-04-17 1993-09-14 General Electric Cgr S.A. Process for representing views of an object
US5261404A (en) 1991-07-08 1993-11-16 Mick Peter R Three-dimensional mammal anatomy imaging system and method
US5265012A (en) 1989-06-12 1993-11-23 Commissariat A L'energie Atomique Method to determine a space from a known discrete space for the reconstruction of bidimensional or tridimensional images, as well as a device to implement and apply the method
US5270926A (en) 1990-12-21 1993-12-14 General Electric Company Method and apparatus for reconstructing a three-dimensional computerized tomography (CT) image of an object from incomplete cone beam projection data
US5283837A (en) 1991-08-27 1994-02-01 Picker International, Inc. Accurate estimation of surface normals in 3-D data sets
US5295488A (en) 1992-08-05 1994-03-22 General Electric Company Method and apparatus for projecting diagnostic images from volumed diagnostic data
US5299288A (en) 1990-05-11 1994-03-29 International Business Machines Corporation Image-directed robotic system for precise robotic surgery including redundant consistency checking
US5322070A (en) 1992-08-21 1994-06-21 E-Z-Em, Inc. Barium enema insufflation system
US5345490A (en) 1991-06-28 1994-09-06 General Electric Company Method and apparatus for converting computed tomography (CT) data into finite element models
US5361763A (en) 1993-03-02 1994-11-08 Wisconsin Alumni Research Foundation Method for segmenting features in an image
US5365927A (en) 1993-11-02 1994-11-22 General Electric Company Magnetic resonance imaging system with pointing device
US5371778A (en) 1991-11-29 1994-12-06 Picker International, Inc. Concurrent display and adjustment of 3D projection, coronal slice, sagittal slice, and transverse slice images
US5442733A (en) 1992-03-20 1995-08-15 The Research Foundation Of State University Of New York Method and apparatus for generating realistic images using a discrete representation
US5458111A (en) 1994-09-06 1995-10-17 William C. Bond Computed tomographic colonoscopy
WO1996013207A1 (fr) 1994-10-27 1996-05-09 Wake Forest University Procede et dispositif de production de restitutions interactives et tridimensionnelles d'une selection d'organes corporels comportant une lumiere aux fins de la simulation d'un mouvement dans cette lumiere
US5548694A (en) * 1995-01-31 1996-08-20 Mitsubishi Electric Information Technology Center America, Inc. Collision avoidance system for voxel-based object representation
US5611025A (en) 1994-11-23 1997-03-11 General Electric Company Virtual internal cavity inspection system
US5623586A (en) 1991-05-25 1997-04-22 Hoehne; Karl-Heinz Method and device for knowledge based representation and display of three dimensional objects
US5630034A (en) 1994-04-05 1997-05-13 Hitachi, Ltd. Three-dimensional image producing method and apparatus
US5699799A (en) 1996-03-26 1997-12-23 Siemens Corporate Research, Inc. Automatic determination of the curved axis of a 3-D tube-shaped object in image volume
WO1998011524A1 (fr) 1996-09-16 1998-03-19 The Research Foundation Of State University Of New York Systeme et procede permettant d'effectuer un examen virtuel en trois dimensions
US5734384A (en) 1991-11-29 1998-03-31 Picker International, Inc. Cross-referenced sectioning and reprojection of diagnostic image volumes
WO1998037517A1 (fr) 1997-02-25 1998-08-27 Wake Forest University Analyse automatique en endoscopie virtuelle
US5986662A (en) 1996-10-16 1999-11-16 Vital Images, Inc. Advanced diagnostic viewer employing automated protocol selection for volume-rendered imaging
WO2000055814A2 (fr) 1999-03-18 2000-09-21 The Research Foundation Of State University Of New York Systeme et procede de realisation d'une segmentation et d'un examen virtuels en trois dimensions
WO2000055812A1 (fr) 1999-03-18 2000-09-21 The Research Foundation Of State University Of New York Systeme et procede de realisation d'un examen virtuel en trois dimensions, d'une navigation et d'une visualisation
US6130671A (en) 1997-11-26 2000-10-10 Vital Images, Inc. Volume rendering lighting using dot product methodology
US6256036B1 (en) * 1997-09-09 2001-07-03 Sanyo Electric Co., Ltd. Three-dimensional modeling apparatus for producing three-dimensional model of object of interest and method therefor
US20010055016A1 (en) 1998-11-25 2001-12-27 Arun Krishnan System and method for volume rendering-based segmentation
US20020164061A1 (en) 2001-05-04 2002-11-07 Paik David S. Method for detecting shapes in medical images

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5825908A (en) * 1995-12-29 1998-10-20 Medical Media Systems Anatomical visualization and measurement system
CA2321049A1 (fr) * 1998-02-23 1999-08-26 Algotec Systems Ltd. Procede et systeme de planification automatique d'un trajet

Patent Citations (66)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4367216A (en) 1979-06-28 1983-01-04 Schering Aktiengesellschaft Triiodinated 5-aminoisophthalic acid derivatives
US4391280A (en) 1980-04-04 1983-07-05 Miller Roscoe E Enema apparata improvements relating to double contrast studies
US4630203A (en) 1983-12-27 1986-12-16 Thomas Szirtes Contour radiography: a system for determining 3-dimensional contours of an object from its 2-dimensional images
US4737921A (en) 1985-06-03 1988-04-12 Dynamic Digital Displays, Inc. Three dimensional medical image display system
US4729098A (en) 1985-06-05 1988-03-01 General Electric Company System and method employing nonlinear interpolation for the display of surface structures contained within the interior region of a solid body
US4710876A (en) 1985-06-05 1987-12-01 General Electric Company System and method for the display of surface structures contained within the interior region of a solid body
US4719585A (en) 1985-08-28 1988-01-12 General Electric Company Dividing cubes system and method for the display of surface structures contained within the interior region of a solid body
US4874362A (en) 1986-03-27 1989-10-17 Wiest Peter P Method and device for insufflating gas
US4751643A (en) 1986-08-04 1988-06-14 General Electric Company Method and apparatus for determining connected substructures within a body
US4791567A (en) 1986-09-15 1988-12-13 General Electric Company Three dimensional connectivity system employing an equivalence schema for determining connected substructures within a body
US4879668A (en) 1986-12-19 1989-11-07 General Electric Company Method of displaying internal surfaces of three-dimensional medical images
US4823129A (en) 1987-02-24 1989-04-18 Bison Instruments, Inc. Analog-to-digital converter
US5095521A (en) 1987-04-03 1992-03-10 General Electric Cgr S.A. Method for the computing and imaging of views of an object
US5245538A (en) 1987-04-17 1993-09-14 General Electric Cgr S.A. Process for representing views of an object
US4831528A (en) 1987-11-09 1989-05-16 General Electric Company Apparatus and method for improvement of 3D images derived from tomographic data
US5170347A (en) 1987-11-27 1992-12-08 Picker International, Inc. System to reformat images for three-dimensional display using unique spatial encoding and non-planar bisectioning
US5038302A (en) 1988-07-26 1991-08-06 The Research Foundation Of State University Of New York Method of converting continuous three-dimensional geometrical representations into discrete three-dimensional voxel-based representations within a three-dimensional voxel-based system
US5023072A (en) 1988-08-10 1991-06-11 University Of New Mexico Paramagnetic/superparamagnetic/ferromagnetic sucrose sulfate compositions for magnetic resonance imaging of the gastrointestinal tract
US4993415A (en) 1988-08-19 1991-02-19 Alliance Pharmaceutical Corp. Magnetic resonance imaging with perfluorocarbon hydrides
US4987554A (en) 1988-08-24 1991-01-22 The Research Foundation Of State University Of New York Method of converting continuous three-dimensional geometrical representations of polygonal objects into discrete three-dimensional voxel-based representations thereof within a three-dimensional voxel-based system
US5056020A (en) 1988-09-16 1991-10-08 General Electric Cge Sa Method and system for the correction of image defects of a scanner due to the movements of the latter
US4984157A (en) 1988-09-21 1991-01-08 General Electric Company System and method for displaying oblique planar cross sections of a solid body using tri-linear interpolation to determine pixel position dataes
US4985856A (en) 1988-11-10 1991-01-15 The Research Foundation Of State University Of New York Method and apparatus for storing, accessing, and processing voxel-based data
US4985834A (en) 1988-11-22 1991-01-15 General Electric Company System and method employing pipelined parallel circuit architecture for displaying surface structures of the interior region of a solid body
US5101475A (en) 1989-04-17 1992-03-31 The Research Foundation Of State University Of New York Method and apparatus for generating arbitrary projections of three-dimensional voxel-based data
US5265012A (en) 1989-06-12 1993-11-23 Commissariat A L'energie Atomique Method to determine a space from a known discrete space for the reconstruction of bidimensional or tridimensional images, as well as a device to implement and apply the method
US5229935A (en) 1989-07-31 1993-07-20 Kabushiki Kaisha Toshiba 3-dimensional image display apparatus capable of displaying a 3-D image by manipulating a positioning encoder
US5006109A (en) 1989-09-12 1991-04-09 Donald D. Douglas Method and device for controlling pressure, volumetric flow rate and temperature during gas insuffication procedures
US5187658A (en) 1990-01-17 1993-02-16 General Electric Company System and method for segmenting internal structures contained within the interior region of a solid object
US5299288A (en) 1990-05-11 1994-03-29 International Business Machines Corporation Image-directed robotic system for precise robotic surgery including redundant consistency checking
US5047772A (en) 1990-06-04 1991-09-10 General Electric Company Digital error correction system for subranging analog-to-digital converters
US5127037A (en) 1990-08-15 1992-06-30 Bynum David K Apparatus for forming a three-dimensional reproduction of an object from laminations
US5204625A (en) 1990-12-20 1993-04-20 General Electric Company Segmentation of stationary and vascular surfaces in magnetic resonance imaging
US5270926A (en) 1990-12-21 1993-12-14 General Electric Company Method and apparatus for reconstructing a three-dimensional computerized tomography (CT) image of an object from incomplete cone beam projection data
US5166876A (en) 1991-01-16 1992-11-24 General Electric Company System and method for detecting internal structures contained within the interior region of a solid object
US5623586A (en) 1991-05-25 1997-04-22 Hoehne; Karl-Heinz Method and device for knowledge based representation and display of three dimensional objects
US5345490A (en) 1991-06-28 1994-09-06 General Electric Company Method and apparatus for converting computed tomography (CT) data into finite element models
US5261404A (en) 1991-07-08 1993-11-16 Mick Peter R Three-dimensional mammal anatomy imaging system and method
US5283837A (en) 1991-08-27 1994-02-01 Picker International, Inc. Accurate estimation of surface normals in 3-D data sets
US5734384A (en) 1991-11-29 1998-03-31 Picker International, Inc. Cross-referenced sectioning and reprojection of diagnostic image volumes
US5371778A (en) 1991-11-29 1994-12-06 Picker International, Inc. Concurrent display and adjustment of 3D projection, coronal slice, sagittal slice, and transverse slice images
US5442733A (en) 1992-03-20 1995-08-15 The Research Foundation Of State University Of New York Method and apparatus for generating realistic images using a discrete representation
US5295488A (en) 1992-08-05 1994-03-22 General Electric Company Method and apparatus for projecting diagnostic images from volumed diagnostic data
US5322070A (en) 1992-08-21 1994-06-21 E-Z-Em, Inc. Barium enema insufflation system
US5361763A (en) 1993-03-02 1994-11-08 Wisconsin Alumni Research Foundation Method for segmenting features in an image
US5365927A (en) 1993-11-02 1994-11-22 General Electric Company Magnetic resonance imaging system with pointing device
US5630034A (en) 1994-04-05 1997-05-13 Hitachi, Ltd. Three-dimensional image producing method and apparatus
US5458111A (en) 1994-09-06 1995-10-17 William C. Bond Computed tomographic colonoscopy
WO1996013207A1 (fr) 1994-10-27 1996-05-09 Wake Forest University Procede et dispositif de production de restitutions interactives et tridimensionnelles d'une selection d'organes corporels comportant une lumiere aux fins de la simulation d'un mouvement dans cette lumiere
US6272366B1 (en) 1994-10-27 2001-08-07 Wake Forest University Method and system for producing interactive three-dimensional renderings of selected body organs having hollow lumens to enable simulated movement through the lumen
US6083162A (en) * 1994-10-27 2000-07-04 Wake Forest University Method and system for producing interactive, three-dimensional renderings of selected body organs having hollow lumens to enable simulated movement through the lumen
US5782762A (en) 1994-10-27 1998-07-21 Wake Forest University Method and system for producing interactive, three-dimensional renderings of selected body organs having hollow lumens to enable simulated movement through the lumen
US5611025A (en) 1994-11-23 1997-03-11 General Electric Company Virtual internal cavity inspection system
US5548694A (en) * 1995-01-31 1996-08-20 Mitsubishi Electric Information Technology Center America, Inc. Collision avoidance system for voxel-based object representation
US5699799A (en) 1996-03-26 1997-12-23 Siemens Corporate Research, Inc. Automatic determination of the curved axis of a 3-D tube-shaped object in image volume
US5971767A (en) * 1996-09-16 1999-10-26 The Research Foundation Of State University Of New York System and method for performing a three-dimensional virtual examination
WO1998011524A1 (fr) 1996-09-16 1998-03-19 The Research Foundation Of State University Of New York Systeme et procede permettant d'effectuer un examen virtuel en trois dimensions
US5986662A (en) 1996-10-16 1999-11-16 Vital Images, Inc. Advanced diagnostic viewer employing automated protocol selection for volume-rendered imaging
US6219059B1 (en) 1996-10-16 2001-04-17 Vital Images, Inc. Interactive control of voxel attributes using selectable characteristics
WO1998037517A1 (fr) 1997-02-25 1998-08-27 Wake Forest University Analyse automatique en endoscopie virtuelle
US6256036B1 (en) * 1997-09-09 2001-07-03 Sanyo Electric Co., Ltd. Three-dimensional modeling apparatus for producing three-dimensional model of object of interest and method therefor
US6130671A (en) 1997-11-26 2000-10-10 Vital Images, Inc. Volume rendering lighting using dot product methodology
US20010055016A1 (en) 1998-11-25 2001-12-27 Arun Krishnan System and method for volume rendering-based segmentation
WO2000055814A2 (fr) 1999-03-18 2000-09-21 The Research Foundation Of State University Of New York Systeme et procede de realisation d'une segmentation et d'un examen virtuels en trois dimensions
WO2000055812A1 (fr) 1999-03-18 2000-09-21 The Research Foundation Of State University Of New York Systeme et procede de realisation d'un examen virtuel en trois dimensions, d'une navigation et d'une visualisation
US20020164061A1 (en) 2001-05-04 2002-11-07 Paik David S. Method for detecting shapes in medical images

Non-Patent Citations (60)

* Cited by examiner, † Cited by third party
Title
80th Scientific Assembly and Annual Meeting Nov. 27-Dec. 2, 1994, Radiology Society of North America Founded in, InfoRAD Exhibits.
A. Viswambharan et al., "Virtual Colonoscopy: Three-dimensional Reconstruction of the Mucosal Surface of the Colon", Conf. of Radiological Society of North America (RSNA), Dec. 1996, pp. 565 (Scientific Merit Award).
Adam L. Penenberg, "From Stony Brook, a New Way to Examine Colons, Externally," The New York Times, p. 6 (1996).
Burgard W. et al., "Active mobile robot localization by entrophy minimization", Proceedings second euromicro workshop on advanced mobile robots, pp. 155-162, 1997.
Chen et al., "A Fast Algorithm to Generate Centerline for Virtual Colonscopy", SPIE Conference, Feb. 12-18, 2000.
Chen et al., "A tree-branch searching, multiresolution approach to skeletonization for virtual endoscopy".
Chen et al., "MRI-Based Virtual Cystoscopy: The image segmentation and visualization", SPIE Conference, Feb. 12-18, 2000.
Chen et al., "Virtual Laryngoscopy: Feasibility Studies by CT and MRI", IEEE Medical Imaging Conference, Nov. 1999.
Chen et al., A multi-scan MRI-based virtual cystoscopy, Feb 2000.
D. Chen et al. "A tree-branch searching, multi-resolution approach to skeletonization for virtual endoscopy", SPIE Medical Imaging 2000, Feb. 2000.
D. Chen et al., "A Novel Approach to Extract Colon Lumen from CT Images for Virtual Colonoscopy" IEEE Transactions on Medical Imaging, vol. 19, No. 12, Dec. 2000, pp. 1220-1226.
D. Chen et al., "MR Imaging and Segmentation of the Colon Wall for Virtual Colonscopy", Soc. Magn. Reson. Medicine, vol. 3, pp. 2203.
David J. Vining, "Virtual Colonscopy," Advance for Administrators in Radiology, pp. 50-52 (1998).
Hagen H. et al., "Methods for Surface Interrogation", Proceedings of the Conference on Visulatization, vol. CONF 1, pp. 187-193, 1990.
Holzapfel G A, et al., "Large strain analysis of soft biological membrances: formulation and finite element analysis", Computer Methods in Applied Mechanics and Engineering, vol. 132, No. 1-2, pp. 45-61, 1996.
Hong et al., "3D Reconstruction and Visualization of the Inner Surface of the Colon from Spiral CT Data," IEEE, pp. 1506-1510 (1997).
Hong et al., "3D Virtual Colonscopy," 1995 Biomedical Visualization Proceedings, pp. 26-32 and 83 (1995).
I. Bitter et al., "Penallized-Distance Volumetric Skeleton Algorithm", IEEE Transactions on Visualization and Computer Graphics, vol. 7, No. 3, Jul.-Sep. 2001, pp. 195-206.
K. Kreeger et al., "Perspective Virtual Endoscopy with VolumePro Parallel Rendering", Center for Visual Computing and Department of Computer Science, pp. 1-8.
K. Kreeger, et al., "Volume Rendering for Virtual Colonoscopy on an Affordable PC", Second International Symposium on Virtual Colonoscopy, Boston, MA, Oct. 2000.
Kaufman A., Wan M., "Disobstruction of Colon Wall Collapse", Project Description, online www.cs.sunysb.edu, Jan. 1999.
Kaye J. et al., "A 3D virtual environment for modeling mechanical cardiopulmonary interactings", CVRMED-MRCAS '97, pp. 389-398, 1997.
L. Hong et al., "Physcially-Based Interactive Navigation", Technical Report TR.96.01.09, Computer Science Department, SUNY at Stony Brook, Jan. 1996.
L. Hong et al., "Virtual Voyage: Interactive Navigation in the Human Colon", Proc. ACM SIGGRAPH '97, Aug. 1997, pp. 27-34.
L. Hong et al., "Visible Human Virtual Colonoscopy", Conference of National Library of Medicine Visible Human Project, Oct. 1996, pp. 29-30.
Liang Z et al., "Inclusion of a priori information in segmentation of colon lumen for 3D virtual colonscopy", 1997 IEEE Nuclear Science Symposium Conference Record, pp. 1423-1427, vol. 2.
Liang Z. et al., "Feasibility Studies on Extracting Bladder Wall from MR Images for Virtual Cystoscopy".
M. Sato et al., "An automatic colon segmentation for 3D virtual colonoscopy", IEICE Trans. Information and Systems, vol. E84-D, No. 1, Jan. 2001, pp. 201-208.
M. Wan et al., "3D Virtual Colonoscopy with Real-time Volume Rendering", SPIE Medical Imaging 2000, Feb. 2000.
M. Wan et al., "Boundary Cell-Based Acceleration for Volume Ray Casting", Computer & Graphices, vol. 22, No. 6, 1998, pp. 715-721.
M. Wan et al., "Distance-Field Based Skeletons for Virtual Navigation", Visualization 2001, San Diego, CA, Oct. 2001.
M. Wan et al., "Volume Rendering Based Interactive Navigation within the Human Colon", IEEE Visualization '99 conference, San Francisco, CA, Oct, 1999, pp. 397-400.
M. Wax et al., "Advancing Virtural Colonoscopy to Practice", International Workshop on 3D Imaging and Virtual Endoscopy, Feb. 2000.
M. Wax et al., "Electronic Colon Cleansing for Virtual Colonoscopy", Presentation at the first Int'l. Conf. on Virtual Colonoscopy, Boston, MA, Oct. 1998.
M. Wax et al., "Virtual Colonoscopy-CT Contrast Agent", Second International Symposium on Virtual Colonoscopy, Boston, MA, Oct. 2000.
Pai D.K. et al., "Multiresolution Rough Terrain Motion Planning", IEEE Transactions on Robotics and Automatic, vol. 14, No. 1, pp. 19-33, 1998.
Pending application with common assignee and potentially related subject matter-U.S. Appl. No. 10/182,217.
Pending application with common assignee and potentially related subject matter-U.S. Appl. No. 10/246,015.
Pending application with common assignee and potentially related subject matter-U.S. Appl. No. 10/246,070.
Pending application with common assignee and potentially related subject matter-U.S. Appl. No. 10/297,349.
Pending application with common assignee and potentially related subject matter-U.S. Appl. No. 10/380,211.
Pending application with common assignee and potentially related subject matter-U.S. Appl. No. 11/613,283.
Pending application with common assignee and potentially related subject matter-U.S. Appl. No. 11/613,306.
R. Chiou et al., "Interactive Fly-Path Planning Using Potential Fields and Cell Decomposition for Virtual Endoscopy", IEEE Trans. Nuclear Sciences, vol. 46, No. 4, Aug. 1999, pp. 1045-1049.
R. Chiou et al., "Interactive Path Planning for Virtual Endoscopy", Conf. Record IEEE NSS-MIC, Nov. 1998.
R. Chiou et al., "Unified Analysis, Modeling, Matching and Synthesis for CT Color Texture Mapping from the Visible Human Dataset", The Second Visible Human Project Conf., Bethesda, MD, Oct. 1998.
R. Chiou et al., "Volume Segmentation and Rendering of Mixtures of Materials for Virtual Colonoscopy", SPIE Medical Imaging '99, Feb. 1999, pp. 133-138.
Richard Robb, "Virtual (Computed) Endoscopy: Development and Evaluation Using the Visible Human Datasets", Oct. 7-8, 1996. www.mayo.edu.
S. Lakare et al., "3D Digital Cleansing Using Segmentation Rays", IEEE Visualization 2000 Conference Proceedings, ACM/SIGGRAPH Press, pp. 37-44, Oct. 2000.
S. Lakare et al., "Automated Pre-navigation processing for Virtual Colonoscopy", Second International Symposium on Virtual Colonoscopy, pp., Oct. 2000.
Shibolet O et al., "Coloring voxel-based objects for virtual endoscopy", IEEE Symposium on Volume Visualization, Research Triangle, Oct. 1998.
Suya You et al., "Interactive volume rendering for virtual colonoscopy", Proceedings Visualization '97, pp. 433-436, 571.
Taosong He, et al. "Collision Detection for Volumetric Objects", Proceedings of the 8th IEEE Visualization Conference, 1997 1070-2385/97.
Valev et al., "Techniques of CT colongraphy (virtual colonoscopy)", Critical Reviews in Biomedical Engineering, 1999, Begall House, vol. 27, No. 1-2, pp. 1-25.
W. Li et al., "Virtual Colonoscopy Powered by VolumePro", pp. 1-13, month unavailable 1999.
William E. Lorensen, "The Exploration of Cross-Sectional Data with a Virtual Endoscope," Interactive Technology and the New Health Paradigm, IOS Press, pp. 221-230 (1995).
Yaoping Wang et al., "Real-Time Interactive Simulator for Percutaneous Coronary Revascularization Procedures", Computer Aided Surgery, 3:211-227, 1998.
Z. Liang et al., "On Segmentation of Colon Lumen for Virtual Colonoscopy", SPIE Medical Imaging, Feb. 1999, pp. 270-278.
Z. Liang et al., "Virtual Endoscopy in Early Detection of Cancers", Biomedical Imaging Symposium: Visualizing the Future of Biology and Medicine, Washington, D.C., Feb. 1999.
Zhou et al., "Three-Dimensional Skeleton and Centerline Generation Based on an Approximate Minimum Distance Field," The Visual Computer, 14:303-314 (1998).

Cited By (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8135201B2 (en) * 2002-07-08 2012-03-13 Vision Rt Limited Image processing system for use with a patient positioning device
US7889906B2 (en) * 2002-07-08 2011-02-15 Vision Rt Limited Image processing system for use with a patient positioning device
US20110178783A1 (en) * 2002-07-08 2011-07-21 Vision Rt Limited Image processing system for use with a patient positioning device
US20090052760A1 (en) * 2002-07-08 2009-02-26 Vision Rt Limited Image processing system for use with a patient positioning device
US20100208956A1 (en) * 2005-11-30 2010-08-19 The Research Foundation Of State University Of New York Electronic colon cleansing method for virtual colonoscopy
US8452061B2 (en) * 2005-11-30 2013-05-28 The Research Foundation Of State University Of New York Electronic colon cleansing method for virtual colonoscopy
US20100201786A1 (en) * 2006-05-11 2010-08-12 Koninklijke Philips Electronics N.V. Method and apparatus for reconstructing an image
US9865079B2 (en) * 2010-03-31 2018-01-09 Fujifilm Corporation Virtual endoscopic image generated using an opacity curve
US20110242097A1 (en) * 2010-03-31 2011-10-06 Fujifilm Corporation Projection image generation method, apparatus, and program
US9401047B2 (en) * 2010-04-15 2016-07-26 Siemens Medical Solutions, Usa, Inc. Enhanced visualization of medical image data
US20110255763A1 (en) * 2010-04-15 2011-10-20 Siemens Medical Solutions Usa, Inc. Enhanced Visualization of Medical Image Data
TWI419080B (zh) * 2010-12-07 2013-12-11 私立中原大學 用於室內設計色彩調和系統之方法
US9964649B2 (en) 2011-11-30 2018-05-08 Izi Medical Products Packaging for retro-reflective markers
US8672490B2 (en) 2011-11-30 2014-03-18 Izi Medical Products High reflectivity retro-reflective marker
US8662684B2 (en) 2011-11-30 2014-03-04 Izi Medical Products Radiopaque core
US8668345B2 (en) 2011-11-30 2014-03-11 Izi Medical Products Retro-reflective marker with snap on threaded post
US8668344B2 (en) 2011-11-30 2014-03-11 Izi Medical Products Marker sphere including edged opening to aid in molding
US8668343B2 (en) 2011-11-30 2014-03-11 Izi Medical Products Reflective marker with alignment feature
US8668342B2 (en) 2011-11-30 2014-03-11 Izi Medical Products Material thickness control over retro-reflective marker
US8641210B2 (en) 2011-11-30 2014-02-04 Izi Medical Products Retro-reflective marker including colored mounting portion
US9085401B2 (en) 2011-11-30 2015-07-21 Izi Medical Products Packaging for retro-reflective markers
US8651274B2 (en) 2011-11-30 2014-02-18 Izi Medical Products Packaging for retro-reflective markers
US8646921B2 (en) 2011-11-30 2014-02-11 Izi Medical Products Reflective marker being radio-opaque for MRI
US8661573B2 (en) 2012-02-29 2014-03-04 Izi Medical Products Protective cover for medical device having adhesive mechanism
US10307220B2 (en) 2012-07-19 2019-06-04 MRI Interventions, Inc. Surgical navigation devices and methods
US9498290B2 (en) 2012-07-19 2016-11-22 MRI Interventions, Inc. Surgical navigation devices and methods
USD829904S1 (en) 2016-01-13 2018-10-02 MRI Interventions, Inc. Curved bracket for surgical navigation systems
USD824027S1 (en) 2016-01-13 2018-07-24 MRI Interventions, Inc. Fins for a support column for a surgical trajectory frame
USD910173S1 (en) 2016-01-13 2021-02-09 Clearpoint Neuro, Inc. Curved bracket for surgical device
US10376333B2 (en) 2016-01-14 2019-08-13 MRI Interventions, Inc. Devices for surgical navigation systems
US11253333B2 (en) 2016-01-14 2022-02-22 Clearpoint Neuro, Inc. Devices for surgical navigation systems
US9943959B2 (en) * 2016-04-25 2018-04-17 Disney Enterprises, Inc. Map localizing with partially obstructed ranging devices for autonomous robots and vehicles
US20170305013A1 (en) * 2016-04-25 2017-10-26 Disney Enterprises, Inc. Map localizing with partially obstructed ranging devices for autonomous robots and vehicles

Also Published As

Publication number Publication date
WO2002029717A3 (fr) 2002-08-15
JP2007195991A (ja) 2007-08-09
JP2007236929A (ja) 2007-09-20
US7574024B2 (en) 2009-08-11
WO2002029717A2 (fr) 2002-04-11
US20040109603A1 (en) 2004-06-10
US20070003131A1 (en) 2007-01-04
JP2007203082A (ja) 2007-08-16
JP2004522464A (ja) 2004-07-29
EP1337970A4 (fr) 2006-09-20
JP2004518186A (ja) 2004-06-17
EP1402478A2 (fr) 2004-03-31
WO2002029723A9 (fr) 2003-02-20
AU2001296506A1 (en) 2002-04-15
AU2002211391A1 (en) 2002-04-15
EP1402478A4 (fr) 2006-11-02
WO2002029723A1 (fr) 2002-04-11
EP1337970A2 (fr) 2003-08-27

Similar Documents

Publication Publication Date Title
US7706600B2 (en) Enhanced virtual navigation and examination
Tschirren et al. Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans
US8275446B2 (en) Automatic analysis in virtual endoscopy
JP5031968B2 (ja) デジタル腸サブトラクションおよびポリープ検出システムならびに関連技術
EP1791087B1 (fr) Procédé d'attraction du point d'intérêt dans des images numériques
US8682045B2 (en) Virtual endoscopy with improved image segmentation and lesion detection
US20070116357A1 (en) Method for point-of-interest attraction in digital images
US8077948B2 (en) Method for editing 3D image segmentation maps
EP2302595A2 (fr) Système amélioré d'endoscopie virtuelle à segmentation des images et détection des lésions
Yoshida et al. CAD in CT colonography without and with oral contrast agents: progress and challenges
US7684602B2 (en) Method and system for local visualization for tubular structures
WO2001078005A2 (fr) Systeme et procede de rendu et d'analyse d'image tridimensionnelle
WO2000032106A1 (fr) Systeme ameliore d'endoscopie virtuelle a segmentation des images et detection des lesions
JP2004520923A (ja) デジタル画像をセグメント化する方法
Serlie et al. Classifying CT image data into material fractions by a scale and rotation invariant edge model
Dijkers et al. Segmentation and size measurement of polyps in CT colonography
Geng et al. Fully automatic extraction of lung parenchyma from CT scans
Kiraly 3D image analysis and visualization of tubular structures

Legal Events

Date Code Title Description
AS Assignment

Owner name: THE RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KAUFMAN, ARIE E.;LIANG, ZHENGRONG;WAX, MARK R.;AND OTHERS;SIGNING DATES FROM 20031106 TO 20040120;REEL/FRAME:017169/0756

Owner name: THE RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KAUFMAN, ARIE E.;LIANG, ZHENGRONG;WAX, MARK R.;AND OTHERS;REEL/FRAME:017169/0756;SIGNING DATES FROM 20031106 TO 20040120

AS Assignment

Owner name: RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YOR

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KAUFMAN, ARIE E.;LIANG, ZHENGRONG;WAX, MARK R.;AND OTHERS;SIGNING DATES FROM 20031106 TO 20040120;REEL/FRAME:017177/0793

Owner name: RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YOR

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KAUFMAN, ARIE E.;LIANG, ZHENGRONG;WAX, MARK R.;AND OTHERS;REEL/FRAME:017177/0793;SIGNING DATES FROM 20031106 TO 20040120

AS Assignment

Owner name: NAVY, UNITED STATES OF AMERICA, THE, AS REPRESENTE

Free format text: CONFIRMATORY LICENSE;ASSIGNOR:NEW YORK, STATE UNIVERSITY OF;REEL/FRAME:017686/0331

Effective date: 20051114

STCF Information on status: patent grant

Free format text: PATENTED CASE

FPAY Fee payment

Year of fee payment: 4

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1552)

Year of fee payment: 8

FEPP Fee payment procedure

Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

LAPS Lapse for failure to pay maintenance fees

Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

STCH Information on status: patent discontinuation

Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362

FP Lapsed due to failure to pay maintenance fee

Effective date: 20220427